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Nowcasting Chinese GDP: information content of economic and financial data

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  • Matthew Yiu
  • Kenneth Chow

Abstract

This article applies the factor model proposed by Giannone, Reichlin, and Small (2005) on a large data set to nowcast (i.e. current-quarter forecast) the annual growth rate of China's quarterly GDP. The data set contains 189 indicator series of several categories, such as prices, industrial production, fixed asset investment, external sector, money market, and financial market. This article also applies Bai and Ng's criteria (2002) to determine the number of common factors in the factor model. The identified model generates out-of-sample nowcasts for China's GDP with smaller mean-squared forecast errors than those of the random walk benchmark. Moreover, using the factor model, we find that interest rate data is the single most important block of information to improve estimates of current-quarter GDP in China. Other important blocks are consumer and retail prices data and fixed asset investment indicators.

Suggested Citation

  • Matthew Yiu & Kenneth Chow, 2010. "Nowcasting Chinese GDP: information content of economic and financial data," China Economic Journal, Taylor & Francis Journals, vol. 3(3), pages 223-240.
    • Handle: RePEc:taf:rcejxx:v:3:y:2010:i:3:p:223-240
    DOI: 10.1080/17538963.2010.562028
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    Cited by:

    1. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    2. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).

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